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Call for Papers and Posters
Personalized Medicine: from genotypes and molecular phenotypes towards therapy Keynote Speaker: Robert Gentleman
January 3-7, 2014
The Big
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Motivation
Genotyping and large-scale molecular phenotyping are already available for large patient cohorts and will soon become routinely available for all patients. These data are setting the stage for rapid advances in personalized medicine, enabling better disease classification, more precise treatment, and improved screening for disease prevention.
Robust statistical and computational methods for analyzing these data are critical to realizing the promise of personalized medicine. Challenges of interest to this session span from accurate low level analyses of high throughput datasets to identification of causal links between different layers of molecular phenotypes, and incorporating them into diagnostics. The important analysis problems include identifying and correcting for hidden structure, dealing with missing data, data heterogeneity, and addressing the problem of multiple testing. For example, in genome-wide association studies, population structure and family relatedness can reduce power and cause spurious associations. In gene expression studies, experimental artifacts and environmental influences have been shown to corrupt results of naive analyses. For multi-omics data, the number of potential causal links imposes a multiple testing burden insurmountable for all but the strongest signals. Further advances in statistical modeling and machine learning are still needed to realize the promise of personalized medicine of delivering a "computed therapy".
The session focuses on methods to address open and new methodological problems pertaining to various genome-wide data, including rare and common polymorphisms, structural variants, epigenetic scans, multi-omic data, intermediate phenotypes, clinical variables, and disease. We will particularly embrace submissions that span the full range from genotype to intermediate phenotype to disease phenotype. The session is intended to have a broad target audience including method developers and practitioners in the fields of medical and human genetics, statistical genetics and related areas.
Session Topic
We would like to invite contributions with relevance to improving
statistical and computational methodology in personalized medicine
that describe either (1) a new problem including ideas on how to
tackle them, (2) a methodological improvement over solutions to existing
problems alongside empirical evaluation, (3) adaptations of existing
solutions to datasets with real-world scale. We encourage submissions
that span the full range from genotype to intermediate phenotype to
disease phenotype. The focus will be on methods applicable to large,
real-world problems. Both frequentist and Bayesian perspectives will
be welcome.
Examples of topics and problems within the scope of this session include :
- Novel statistical and computational approaches for genome sequence analysis of omics data, such as DNA, RNA and bisulfite sequencing.
- Methodology for making use of rare and low frequency variants arising from whole-genome and exome sequencing: combining information across individuals or within a locus, prioritisation of mutations.
- New statistical and machine learning approaches for Genome-Wide Association Studies (PCA-based approaches, Mixed Model approaches, etc.).
- Gene expression studies: modeling hidden factors, characterizing cell types in heterogeneous tissues, removing confounding effects, inferring the activity of disease-relevant regulators.
- Models for longitudinal personal multi-omic data: high-dimensional time series analysis, disease onset prediction, finding genotype-dependent interactions between phenotypes and environment.
- Predictive models for disease, including biomarker selection and survival time prediction.
- Development of causal models for genotype, gene expression, disease labels and intermediate phenotypes.
- Improvement of existing methods to address the increasing demand for computational efficiency to allow for genome-scale applications.
- Comprehensive evaluation and comparison of existing methods in the context of practical applications.
- Innovative software for personalized medicine: for point-of-care use by physicians, analysis software for consumers and clinical geneticists, prioritisation and visualisation of genetic variation and longitudinal phenotypes for personalised -omics.
Other topics within the subject area are welcome.
Session Co-Chairs
| Oliver Stegle, Ph.D. Max Planck Institutes, Tuebingen oliver.stegle@tuebingen.mpg.de |
Jennifer Listgarten, Ph.D. Microsoft Research (Los Angeles) jennl@microsoft.com |
Steven Brenner, Ph.D. University of California, Berkeley brenner@compbio.berkeley.edu |
Leopold Parts, Ph.D. University of Toronto leopold.parts@utoronto.ca |
Quaid Morris, Ph.D. University of Toronto quaid.morris@utoronto.ca |
Submission Information
Please note that the submitted papers are reviewed and accepted on a competitive basis.
Important Dates
- Paper submissions due: July 31, 2013
- Notification of paper acceptance: September 9, 2013
- Camera-ready final paper deadline: October 1, 2013
- Abstract deadline for unreviewed posters: November 15, 2013
Paper Format
Please see the PSB paper format template and instructions at http://psb.stanford.edu/psb-online/psb-submit.
The file formats we accept are: postscript (*.ps) and Adobe Acrobat (*.pdf)). Attached files should be named with the last name of the first author (e.g. altman.ps or altman.pdf). Hardcopy submissions or unprocessed
Each paper must be accompanied by a cover letter. The cover letter must state the following:
- The email address of the corresponding author.
- The specific PSB session that should review the paper or abstract.
- The submitted paper contains original, unpublished results, and is not currently under consideration elsewhere.
- All co-authors concur with the contents of the paper.
Submitted papers are limited to twelve (12) pages in our publication format. Please format your paper according to instructions found at http://psb.stanford.edu/psb-online/psb-submit/. If figures cannot be easily resized and placed precisely in the text, then it should be clear that with appropriate modifications, the total manuscript length would be within the page limit.